tslm is used to fit linear models to time series including trend and
tslm(formula, data, subset, lambda = NULL, biasadj = FALSE, ...)
an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted.
an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which lm is called.
an optional subset containing rows of data to keep. For best
results, pass a logical vector of rows to keep. Also supports
Box-Cox transformation parameter. If
Use adjusted back-transformed mean for Box-Cox transformations. If transformed data is used to produce forecasts and fitted values, a regular back transformation will result in median forecasts. If biasadj is TRUE, an adjustment will be made to produce mean forecasts and fitted values.
Other arguments passed to
Returns an object of class "lm".
tslm is largely a wrapper for
lm() except that
it allows variables "trend" and "season" which are created on the fly from
the time series characteristics of the data. The variable "trend" is a
simple time trend and "season" is a factor indicating the season (e.g., the
month or the quarter depending on the frequency of the data).
y <- ts(rnorm(120,0,3) + 1:120 + 20*sin(2*pi*(1:120)/12), frequency=12) fit <- tslm(y ~ trend + season) plot(forecast(fit, h=20))